Replication of fifteen loci involved in human plasma protein N-glycosylation in 4,802 samples from four cohorts

Human protein glycosylation is a complex process, and its in vivo regulation is poorly understood. Changes in glycosylation patterns are associated with many human diseases and conditions. Understanding the biological determinants of protein glycome provides a basis for future diagnostic and therapeutic applications. Genome-wide association studies (GWAS) allow to study biology via a hypothesis-free search of loci and genetic variants associated with a trait of interest. Sixteen loci were identified by three previous GWAS of human plasma proteome N-glycosylation. However, the possibility that some of these loci are false positives needs to be eliminated by replication studies, which have been limited so far. Here, we use the largest set of samples so far (4,802 individuals) to replicate the previously identified loci. For all but one locus, the expected replication power exceeded 95%. Of the sixteen loci reported previously, fifteen were replicated in our study. For the remaining locus (near the KREMEN1 gene) the replication power was low, and hence replication results were inconclusive. The very high replication rate highlights the general robustness of the GWAS findings as well as the high standards adopted by the community that studies genetic regulation of protein glycosylation. The fifteen replicated loci present a good target for further functional studies. Among these, eight genes encode glycosyltransferases: MGAT5, B3GAT1, FUT8, FUT6, ST6GAL1, B4GALT1, ST3GAL4, and MGAT3. The remaining seven loci offer starting points for further functional follow-up investigation into molecules and mechanisms that regulate human protein N-glycosylation in vivo

Bidirectional Mendelian Randomization study of personality traits reveals a positive feedback loop between neuroticism and back pain.

We conducted a bidirectional Mendelian randomization study to examine the causal effects of six personality traits (anxiety, neuroticism, extraversion, openness to experience, agreeableness and conscientiousness) on back pain associated with health care use and the causal effect of back pain on the same risk factors. Genetic instruments for the personality traits and back pain were obtained from the largest published genome-wide association studies conducted in individuals of European ancestry. We used inverse weighted variance meta-analysis and Causal Analysis Using Summary Effect for primary analyses and sensitivity analyses to examine evidence for causal associations. We interpreted exposure-outcome associations as being consistent with a causal relationship if results of at least one primary analysis were statistically significant after accounting for multiple statistical testing (p-value < 0.0042), and the direction and magnitude of effect estimates were concordant between primary and sensitivity analyses. We found evidence for statistically significant bidirectional causal associations between neuroticism and back pain, with odds ratio 1.51 (95% confidence interval 1.37; 1.67) of back pain per neuroticism sum score standard deviation, p-value = 7.80e-16; and beta = 0.12, se = 0.04 of neuroticism sum score standard deviation per log odds of back pain, p-value = 2.48e-03. Other relationships did not meet our predefined criteria for causal association. PERSPECTIVE: The significant positive feedback loop between neuroticism and back pain highlights the importance of considering neuroticism in the management of patients with back pain

Evidence of causal effects of blood pressure on back pain and back pain on type II diabetes provided by a bidirectional Mendelian randomization study.

BACKGROUND CONTEXT: Cardiovascular risk factors (hypertension, dyslipidemia, and type II diabetes) have been proposed as risk factors for back pain. However, few longitudinal studies have found significant associations between cardiovascular risk factors and back pain, and these may be explained by confounding or reverse causation. PURPOSE: To examine potential causal effects of cardiovascular risk factors on back pain, and vice versa. STUDY DESIGN: Bidirectional Mendelian randomization (MR) study. PATIENT SAMPLES: Genome-wide association studies (GWAS) with sample sizes between 173,082 and 1,028,947 participants. OUTCOME MEASURES: Outcomes included (1) back pain associated with health care use (BP-HC) in the forward MR; and (2) seven cardiovascular phenotypes in the reverse MR, including 2 measurements used for the evaluation of hypertension (diastolic blood pressure and systolic blood pressure), 4 phenotypes related to dyslipidemia (LDL cholesterol, HDL cholesterol, total cholesterol, and triglycerides), and type II diabetes. METHODS: We used summary statistics from large, publicly available GWAS for BP-HC and the 7 cardiovascular phenotypes to obtain genetic instrumental variables. We examined MR evidence for causal associations using inverse-variance weighted (IVW) analysis, Causal Analysis Using Summary Effect (CAUSE), and sensitivity analyses. RESULTS: In forward MR analyses of seven cardiovascular phenotypes, diastolic blood pressure was associated with BP-HC across all analyses (IVW estimate: OR = 1.10 per 10.5 mm Hg increase [1.04-1.17], p-value = .001), and significant associations of systolic blood pressure with BP-HC were also found (IVW estimate: OR = 1.09 per 19.3 mm Hg increase [1.04-1.15], p-value = .0006). In reverse MR analyses, only type II diabetes was associated with BP-HC across all analyses (IVW estimate: OR = 1.40 [1.13-1.73], p-value = .002). CONCLUSIONS: These findings from analyses of large, population-based samples indicate that higher blood pressure increases the risk of BP-HC, and BP-HC itself increases the risk of type II diabetes

Causal effects of psychosocial factors on chronic back pain: a bidirectional Mendelian randomisation study.

PURPOSE: Risk factors for chronic back pain (CBP) may share underlying genetic factors, making them difficult to study using conventional methods. We conducted a bi-directional Mendelian randomisation (MR) study to examine the causal effects of risk factors (education, smoking, alcohol consumption, physical activity, sleep and depression) on CBP and the causal effect of CBP on the same risk factors. METHODS: Genetic instruments for risk factors and CBP were obtained from the largest published genome-wide association studies (GWAS) of risk factor traits conducted in individuals of European ancestry. We used inverse weighted variance meta-analysis (IVW), Causal Analysis Using Summary Effect (CAUSE) and sensitivity analyses to examine evidence for causal associations. We interpreted exposure-outcome associations as being consistent with a causal relationship if results with IVW or CAUSE were statistically significant after accounting for multiple statistical testing (p < 0.003), and the direction and magnitude of effect estimates were concordant between IVW, CAUSE, and sensitivity analyses. RESULTS: We found evidence for statistically significant causal associations between greater education (OR per 4.2 years of schooling = 0.54), ever smoking (OR = 1.27), greater alcohol consumption (OR = 1.29 per consumption category increase) and major depressive disorder (OR = 1.41) and risk of CBP. Conversely, we found evidence for significant causal associations between CBP and greater alcohol consumption (OR = 1.19) and between CBP and smoking (OR = 1.21). Other relationships did not meet our pre-defined criteria for causal association. CONCLUSION: Fewer years of schooling, smoking, greater alcohol consumption, and major depressive disorder increase the risk of CBP. CBP increases the risk of greater alcohol consumption and smoking